• ✔ This project presents a Next Word Prediction application
  
• ✔ Developed using R and Shiny
  
• ✔ Provides intelligent and context-based word suggestions
  
• ✔ Demonstrates key Natural Language Processing concepts

Key Idea: The application predicts the next word based on learned text patterns.

• ✔ Typing complete sentences can be time-consuming
  
• ✔ Users require quick and relevant suggestions
  
• ✔ Objective: Predict the most probable next word
  
• ✔ Improve typing efficiency and user experience

Key Idea: Faster prediction enhances user productivity.

• ✔ Uses a bigram-based language model
  
• ✔ Extracts the last word from user input
  
• ✔ Matches patterns from trained dataset
  
• ✔ Applies frequency-based ranking
  
• ✔ Outputs best prediction and top 3 suggestions

Key Idea: Predictions are based on frequency of word occurrence.

• ✔ User enters text (e.g., “I love”)
  
• ✔ App predicts next word (e.g., “coding”)
  
• ✔ Displays best prediction and alternative suggestions
  
• ✔ Designed with a clean and interactive interface

Key Idea: Simple interface with fast and meaningful output.

• ✔ Successfully built a word prediction system
  
• ✔ Deployed as a Shiny web application
  
• ✔ Provides quick and relevant suggestions
  
• ✔ Can be improved using larger datasets and advanced models

Key Idea: Demonstrates a practical application of NLP concepts.